The Excel CORREL Function

The Pearson product-moment correlation coefficient is a statistical measurement of the correlation
(linear association) between two sets of values.

The Pearson product-moment correlation coefficient for two sets of values, x and y, is
given by the formula :

where x and y
are the sample means of the two arrays of values.

If the value of r is close to +1, this indicates a strong positive correlation, and if
r is close to -1, this indicates a strong negative correlation.

More information on the Pearson Product-Moment Correlation Coefficient is given on
Wikipedia

Basic Description

The Excel CORREL function calculates the Pearson Product-Moment Correlation Coefficient for two sets of values.

The format of the function is :

CORREL( array1, array2 )

Where array1 is a set of independent variables and array2 is a set of dependent variables.
These arrays should be of equal length.

Excel Correl Function vs. Excel Pearson Function

The Excel Correl function is the same as the
Excel Pearson Function, except that,
in earlier versions of Excel (earlier than Excel 2003), the Pearson function may exhibit some rounding errors.

Therefore, if you are using an earlier version of Excel than Excel 2003, you should use the Correl function
in preference to the Pearson function. In later versions of Excel, both functions should give the same results.

Excel Correl Function Example

A

B

1

x

y

2

2

22.90

3

10

45.78

4

7

33.49

5

17

49.77

6

14

40.94

7

16

36.18

8

8

21.05

9

12

50.57

10

11

31.32

11

15

53.76

12

18

55.66

13

3

27.61

14

4

11.15

15

1

10.11

16

6

37.90

17

5

31.08

18

13

45.48

19

19

63.83

20

20

63.60

21

9

27.01

Columns A and B of the spreadsheet on the right contain two arrays of values. These are shown in the chart below:

The Pearson Product-Moment Correlation Coefficient of the values in columns A and B of the spreadsheet can
be calculated using the Excel Correl function, as follows:

=CORREL( A2:A21, B2:B21 )

This gives the result 0.870035104, which indicates a strong positive correlation between the two sets of values.